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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRSDate not supplied

Single and Multi-Node Modeling of Direct, Submerged, and Self-Pressurization of A Cryogenic Propellant Tank Using Nodal Tools

The pressurization of cryogenic propellant tanks will always be an important process so long as cryogenic liquids are being considered as fuel sources or used for other in-space applications. Pressure control of the tank ullage is necessary for managing propellant flowrates to an engine or a receiver tank, and modeling of the process is used to predict the pressurant requirements and the amount of propellant boiloff. Direct ullage pressurization is the more traditional approach to tank pressurization, as the physics are straight-forward, and ample test (flight) data have been collected and analyzed over the past several decades. Submerged injection pressurization is an alternate method for tank pressurization and has been shown to reduce pressurant requirements, subcool the propellant, and reduce the risk of ullage collapse. Additionally, the pressurant gas entering the ullage is usually much colder when using the submerged pressurization approach, resulting in reduced propellant boiloff. These benefits are at the expense of vaporizing a small percentage of the propellent. Both tank pressurization methods are viable options for current and future space missions, and it is important to have the capability of analyzing the tank ullage conditions for both approaches. Our previous work has demonstrated the development of a Generalized Fluid System Simulation Program (GFSSP) model, which contains a thermodynamic equilibrium heat and mass transfer subroutine capable of effectively analyzing both direct and submerged pressurization systems [1-2]. This subroutine has most recently been enhanced to include the non-equilibrium effect of pressurant dissolution into the propellant. To date the ullage has always been represented as a single node, and although the simulated single-node temperatures have good comparison with the volume-averaged ullage temperatures computed from test data, the physics of the thermal stratification in the ullage were never captured, and adjustment factors in the model were required. The purpose of this paper is to introduce the development of a multi-node ullage model using GFSSP and to discuss the improvements of the simulated ullage temperature distribution and its resulting effects on ullage heat transfer processes. Test data from the Cryogenic Propellant Storage and Transfer Engineering Developmental Unit (CPST EDU) was used for model validation. For additional comparison, a Thermal Desktop (TD) model was also developed to analyze the CPST EDU direct ullage pressurization tests using both a single node and multi-node approach. The model includes the direct pressurant line, vent line, fill/drain line, and a TD FloCAD Compartment. The TD FloCAD Compartment is employed to represent the liquid and ullage as single volumes inside the tank, to include a liquid/vapor interface, and to generate network level objects such as lumps (analogous to nodes in GFSSP), paths, and ties between the fluid and thermal elements. An established heat load on the model tank was leveraged from a pre-existing higher-fidelity model correlated to CPST EDU test data.

pressurization↗
NASA NTRS1999

A Study of Mars Dust Environment Simulation at NASA Johnson Space Center Energy Systems Test Area Resource Conversion Test Facility

The dust environment on Mars is planned to be simulated in a 20 foot thermal-vacuum chamber at the Johnson Space Center, Energy Systems Test Area Resource Conversion Test Facility in Houston, Texas. This vacuum chamber will be used to perform tests and study the interactions between the dust in Martian air and ISPP hardware. This project is to research, theorize, quantify, and document the Mars dust/wind environment needed for the 20 foot simulation chamber. This simulation work is to support the safety, endurance, and cost reduction of the hardware for the future missions. The Martian dust environment conditions is discussed. Two issues of Martian dust, (1) Dust Contamination related hazards, and (2) Dust Charging caused electrical hazards, are of our interest. The different methods of dust particles measurement are given. The design trade off and feasibility were studied. A glass bell jar system is used to evaluate various concepts for the Mars dust/wind environment simulation. It was observed that the external dust source injection is the best method to introduce the dust into the simulation system. The dust concentration of 30 Mg/M3 should be employed for preparing for the worst possible Martian atmosphere condition in the future. Two approaches thermal-panel shroud for the hardware conditioning are discussed. It is suggested the wind tunnel approach be used to study the dust charging characteristics then to be apply to the close-system cyclone approach. For the operation cost reduction purpose, a dehumidified ambient air could be used to replace the expensive CO2 mixture for some tests.

Chen, Yuan-Liang Albert↗
NASA NTRS1993

Improving the reconstruction of the velocity potential and primordial density fluctuations by choice of smoothing windows

Recently considerable attention has been focused on improving algorithms for restoring primordial density fluctuations in the universe or investigating large-scale velocity fields by going to higher order approximations relating nonlinear states to their initial conditions. An alternative approach is to investigate the use of alternative smoothing windows within the context of first-order approximations. I present evidence that the universally used Gaussian smoothing window is far from optimal. A sharp truncation P(k) = 0 for k greater than k(c) leads to a much more direct connection to initial conditions for either 'Gaussianization' methods or use of the Zel'dovich approximation, as discussed in the text.

Melott, Adrian L.↗
NASA NTRS2019

Reinforcing Additives for Ice Adhesion Reduction Coatings

Adhesion of contaminants has been identified as a ubiquitous issue for aeronautic exterior surfaces. In-flight icing is particularly hazardous for all aircraft and can be experienced throughout the year under the appropriate environmental conditions. On larger vehicles, the accretion of ice could result in loss of lift, engine failure, and potentially loss of vehicle and life were it not for active deicing or anti-icing equipment. Smaller vehicles though cannot support the mass and mechanical complexity of active ice mitigating systems and thus must rely upon passive approaches or avoid icing conditions altogether. One approach that may be applicable to all aircraft is the use of coatings. Durability remains an issue and has prevented realization of coatings for leading edge contamination mitigation. In this work, epoxy coatings were generated as a passive approach for ice adhesion mitigation and methods to improve durability were evaluated. Highly cross-linked epoxy systems can be extremely rigid, which could have deleterious consequences regarding application as a leading edge coating. Incorporation of flexible species, such as poly(ethylene glycol) may improve coating toughness.8 Additionally, core-shell rubber (CSR) particles have been utilized to improve fracture toughness of epoxies.9 Both of these more established additives are investigated in this work. An emerging additive that is also evaluated here is holey graphene. This nanomaterial possesses many of the advantageous properties of graphene (excellent mechanical properties, thermal and electrical conductivity, large surface area, etc.) while also exhibiting behaviors associated with flexible, porous materials (i.e., compressibility, increased permeation, etc.). Holey graphene, HG, was synthesized by the oxidation of defect-rich sites on graphene sheets through controlled thermal expo-sure.10 It is envisioned that the porous nature of HG would allow resin penetration through the graphitic plane, resulting in better interfacial interaction and therefore better translation of the nanomaterial’s properties to the surrounding matrix.

Wohl, Christopher J↗
NASA NTRS2007

Identification and Control of Aircrafts using Multiple Models and Adaptive Critics

We compared two possible implementations of local linear models for control: one approach is based on a self-organizing map (SOM) to cluster the dynamics followed by a set of linear models operating at each cluster. Therefore the gating function is hard (a single local model will represent the regional dynamics). This simplifies the controller design since there is a one to one mapping between controllers and local models. The second approach uses a soft gate using a probabilistic framework based on a Gaussian Mixture Model (also called a dynamic mixture of experts). In this approach several models may be active at a given time, we can expect a smaller number of models, but the controller design is more involved, with potentially better noise rejection characteristics. Our experiments showed that the SOM provides overall best performance in high SNRs, but the performance degrades faster than with the GMM for the same noise conditions. The SOM approach required about an order of magnitude more models than the GMM, so in terms of implementation cost, the GMM is preferable. The design of the SOM is straight forward, while the design of the GMM controllers, although still reasonable, is more involved and needs more care in the selection of the parameters. Either one of these locally linear approaches outperform global nonlinear controllers based on neural networks, such as the time delay neural network (TDNN). Therefore, in essence the local model approach warrants practical implementations. In order to call the attention of the control community for this design methodology we extended successfully the multiple model approach to PID controllers (still today the most widely used control scheme in the industry), and wrote a paper on this subject. The echo state network (ESN) is a recurrent neural network with the special characteristics that only the output parameters are trained. The recurrent connections are preset according to the problem domain and are fixed. In a nutshell, the states of the reservoir of recurrent processing elements implement a projection space, where the desired response is optimally projected. This architecture trades training efficiency by a large increase in the dimension of the recurrent layer. However, the power of the recurrent neural networks can be brought to bear on practical difficult problems. Our goal was to implement an adaptive critic architecture implementing Bellman s approach to optimal control. However, we could only characterize the ESN performance as a critic in value function evaluation, which is just one of the pieces of the overall adaptive critic controller. The results were very convincing, and the simplicity of the implementation was unparalleled.

Principe, Jose C.↗
NASA NTRS2000

Flame Design: A Novel Approach Developed to Produce Clean, Efficient Diffusion Flames

Soot formation and flame extinction are vital concerns in the combustion of fossil fuels. In particular, soot is responsible for pollutant emissions, and extinction can cause inefficient or unstable burning. Normal-gravity experiments have demonstrated that flames can be designed to improve both characteristics by redirecting some or all of the nitrogen from the oxidizer into the fuel. Such nitrogen exchange can produce permanently blue flames, which are soot free under all possible flame conditions. Furthermore, this approach can lead to stronger, extinction-resistant flames. Past investigations of nitrogen exchange were unable to identify the physical mechanisms responsible for its benefits because these mechanisms cannot be isolated when normal-gravity flames are studied. In contrast, the Diffusion Flame Extinction and Soot Inception (DESI) experiment considers spherical flames, where nearly perfect spherical symmetry affords new levels of control. Because of buoyancy, spherical flames cannot be created in Earth s gravity. DESI was conceived by principal investigator Professor R.L. Axelbaum of Washington University in St. Louis. Tests to date have utilized the 2.2-Second Drop Tower at the NASA Glenn Research Center at Lewis Field. The experiment is slated for testing aboard the International Space Station in a few years. Two mechanisms have been proposed to explain the connection between nitrogen exchange and permanently blue flames. These are the structure (chemical effects) and hydrodynamics (flow direction and speed). In normal-gravity flames, the structure and hydrodynamics are coupled, since nitrogen exchange simultaneously modifies both. Spherical microgravity flames, on the other hand, allow independent control of these factors. Specifically, structure can be modified via nitrogen exchange, and flow direction can be reversed by swapping the ambient and burner-feed gases. In DESI, these variations can be accomplished without changing the theoretical flame temperature.

Axelbaum, Richard L.↗
NASA NTRS1991

A two-dimensional, time-dependent, near-earth magnetotail

A kinetic approach is presented for obtaining slowly time-dependent, self-consistent plasma, and magnetic field configurations for this region, using anisotropic particle distributions. At present, a 2D configuration is used. The time variation of the plasma/field configuration is assumed to be driven by a slowly varying, externally imposed electric field (representing, for example, a change in solar wind conditions). The numerical approach involves solving a 2D nonlinear Poisson equation for the magnetic vector potential at each time step. The local current density is calculated from particle velocity distributions under the assumption of adiabatic particle motion. The obtained equations of state are compared with those of double-adiabatic theory. Numerical examples of self-consistent responses of the near-earth plasma and field to an externally imposed electric field pulse are presented.

Whipple, Elden↗
NASA NTRS1972

Predicted upwash angles at engine inlets for STOL aircraft

Upwash angles were predicted for a STOL lifting system by using a two-dimensional potential flow analysis. Upwash angles are presented for distances ahead of the wing leading edge of 50, 75, and 100 percent of wing chord. The upwash angle was determined to be insensitive to the vertical location of the engine inlet. For a wide range of takeoff and landing conditions, the upwash angle was found to be a function of the total two-dimensional lift coefficient. Upwash angles, along with typical flow fields, are presented for a range of total two-dimensional lift coefficients from 2 to 12. Three-dimensional effects were considered in estimating upwash angles for an unswept-wing externally blown flap aircraft. For this STOL configuration, effective upwash angles during takeoff, approach, and waveoff conditions were found to be 22 deg, 26 deg, and 36 deg, respectively.

Albers, J. A.↗
NASA NTRS2006

Airport Remote Tower Sensor Systems

Networks of video cameras, meteorological sensors, and ancillary electronic equipment are under development in collaboration among NASA Ames Research Center, the Federal Aviation Administration (FAA), and the National Oceanic Atmospheric Administration (NOAA). These networks are to be established at and near airports to provide real-time information on local weather conditions that affect aircraft approaches and landings. The prototype network is an airport-approach-zone camera system (AAZCS), which has been deployed at San Francisco International Airport (SFO) and San Carlos Airport (SQL). The AAZCS includes remotely controlled color video cameras located on top of SFO and SQL air-traffic control towers. The cameras are controlled by the NOAA Center Weather Service Unit located at the Oakland Air Route Traffic Control Center and are accessible via a secure Web site. The AAZCS cameras can be zoomed and can be panned and tilted to cover a field of view 220 wide. The NOAA observer can see the sky condition as it is changing, thereby making possible a real-time evaluation of the conditions along the approach zones of SFO and SQL. The next-generation network, denoted a remote tower sensor system (RTSS), will soon be deployed at the Half Moon Bay Airport and a version of it will eventually be deployed at Los Angeles International Airport. In addition to remote control of video cameras via secure Web links, the RTSS offers realtime weather observations, remote sensing, portability, and a capability for deployment at remote and uninhabited sites. The RTSS can be used at airports that lack control towers, as well as at major airport hubs, to provide synthetic augmentation of vision for both local and remote operations under what would otherwise be conditions of low or even zero visibility.

Maluf, David A.↗
NASA NTRS1972

On self-similar blast waves headed by the Chapman-Jouguet detonation.

Consideration of the whole class of self-similar solutions for blast waves bounded by Chapman-Jouguet detonations that propagate into a uniform, quiescent, zero counterpressure atmosphere of a perfect gas with constant specific heats. Since such conditions can be approached quite closely by some actual chemical systems at NTP, this raises the interesting possibility of the existence of Chapman-Jouguet detonations of variable velocity. The principal virtue of the results presented is, however, more of theoretical significance. They represent the limiting case for all the self-similar blast waves headed by gasdynamic discontinuities associated with a deposition of finite amounts of energy, and they exhibit some unique features owing to the singular nature of the Chapman-Jouguet condition.

Oppenheim, A. K.↗
NASA NTRS1982

The baroclinic instability of highly structured one-dimensional basic states

A frictionless, adiabatic, quasi-geostrophic model on a beta-plane was employed to examine the baroclinic instability of highly structured one-dimensional basic states. Definitions of the model eigenvalue equation, the boundary conditions, and the fluxes and energetics are provided, and highly structured average wind speed and temperature profiles were selected to represent a wide range of latitudes. Attention was given to the instability source, wavelength, growth rate, phase velocity, steering levels, and the vertical structure of their amplitude, phase, meridional entropy transport, and conversion of potential-to-kinetic energy. Green modes, Charney-Eady modes, and the modes defined in the paper are examined in connection with the highly structured profiles. The eigenvalue approach is shown to be superior to the numerical time integration approach and necessary conditions for instabilities are defined.

Fullmer, J. W. A.↗
NASA NTRS1957

Extended Operation of Turbojet Engine with Pentaborane

A full-scale turbojet engine was operated with pentaborane fuel continuously for 22 minutes at conditions simulating flight at a Mach number of 0.8 at an altitude of 50,000 feet. This period of operation is approximately three times longer than previously reported operation times. Although the specific fuel consumption was reduced from 1.3 with JP-4 fuel to 0.98 with pentaborane, a 13.2-percent reduction in net thrust was also encountered. A portion of this thrust loss is potentially recoverable with proper design of the engine components. The boron oxide deposition and erosion processes within the engine approached an equilibrium condition after approximately 22 minutes of operation with pentaborane.

Useller, James W↗
NASA NTRS2017

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗
NASA NTRS2017

Multi-Objective Reinforcement Learning-based Deep Neural Networks for Cognitive Space Communications

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

space archtiecture↗
NASA NTRSDate not supplied

Cryogenically-Operable Electronics for Surviving the Lunar Night

Current solar-powered robotic lunar landers and rovers have not demonstrated survivability of the extreme cold temperatures seen during the 354-hour lunar night. To address this capability gap, we have been investigating the feasibility of a passive hibernation approach to enable low-cost solar- and battery-powered missions to operate over multiple lunar cycles. This strategy relies on isolating the batteries from the main bus during the lunar night and allowing cells to freeze as temperatures descend as low as 50K. The entire power architecture remains in a hibernation state with no electrical activity until lunar dawn. When the sun returns over the horizon, the now-illuminated solar arrays begin generating power. In order to manage the array power, architecture consisting of cryogenically-operable COTS electronics must be utilized. This architecture will distribute and control power to subsystems - importantly controlling heaters to bring the frozen lithium-ion battery cells to normal operating conditions. This alternative approach to lunar operations will enable low-cost commercial lunar landers and payloads to passively survive the night and continue to operate over multiple lunar cycles without a significant impact to cost or payload mass. Research last year focused on creating a power supply that was capable of operation at cryogenic temperatures. At the end of FY23, our team successfully designed and manufactured a Sequential Switching Shunt Regulator (S3R) that is operational in a cryogenic vacuum chamber. It is capable of full operation down to the coldest lunar night temperatures (~50K). Our presentation will provide an overview of the Lunar Hibernation strategy but will focus mainly on the technical details of this cryogenically-operable shunt regulator and test results.

Cryogenic↗
NASA NTRS2024

Hybrid Thermally Efficient Core (HyTEC) HyTEC Phase 1 – Combustor Final Report

The objective of the HyTEC – Combustor Technology project is to develop technology for a compact, low emissions, rich-burn combustor that maintains a high-level of durability. To accomplish this, the combustor will incorporate CMC liners and a CMC Dome to enable improved air utilization for mixing and NOx reduction. In particular, three technology areas were matured: metallic swirler attachment to the CMC dome, Nickel diffusion in CMC, and EBC advancements with improved durability. The maturation of these technology areas is critical to successfully designing a combustor for an engine intended to demonstrate increased thermal efficiency with integrated high-power density-core engine technologies. As part of the project, multiple swirler attachment architectures were matured through the design process, manufactured, and tested in simulated engine conditions. These architectures utilized two different approaches to attachment: a pressure loaded approach and a clamped approach. Each approach required testing at simulated engine conditions to mature the technology. These tests were developed to ensure that the probable failure mechanisms for each architecture were assessed relative to its long-term durability. After successfully testing both approaches, the pressure loaded approach was chosen based on its simplicity and its similarity to the attachment approach used on lean burn combustors. Finally, this successful testing resulted in the swirler attachment technology achieving TRL 4 status. Another aspect of concern with the metallic swirler attachment is the potential for nickel diffusion into the CMC to cause durability shortfalls. A series of tests were completed to understand both the amount of nickel that is expected to diffuse into the CMC and the effect this diffusion will have on mechanical properties of the CMC. After successfully completing this testing, the reduction in local mechanical properties was found to not have an impact on the overall durability of the CMC Dome. To further improve the overall durability, three different EBC coating architectures were also studied. One of these coatings being the current state of the art for CMC liners with the other two being proposed improvements. Coupons were produced using each coating and subjected to a series of laboratory testing. One coating was found to have an overall superior durability in laboratory testing and survived rig testing without indication of degradation. This successful testing resulted in the EBC technology achieving TRL 5 status. Overall, a design approach was successfully down-selected that achieves both the TPM requirements and the need for TRL 4+ status. This design incorporates a pressure loaded swirler attachment with an improved EBC coating (Architecture 1). This combination allows the continued use of a CMC dome and results in an improved durability for the proposed compact core combustor.

CMC↗
NASA NTRS2004

Adjoint Algorithm for CAD-Based Shape Optimization Using a Cartesian Method

Adjoint solutions of the governing flow equations are becoming increasingly important for the development of efficient analysis and optimization algorithms. A well-known use of the adjoint method is gradient-based shape optimization. Given an objective function that defines some measure of performance, such as the lift and drag functionals, its gradient is computed at a cost that is essentially independent of the number of design variables (geometric parameters that control the shape). More recently, emerging adjoint applications focus on the analysis problem, where the adjoint solution is used to drive mesh adaptation, as well as to provide estimates of functional error bounds and corrections. The attractive feature of this approach is that the mesh-adaptation procedure targets a specific functional, thereby localizing the mesh refinement and reducing computational cost. Our focus is on the development of adjoint-based optimization techniques for a Cartesian method with embedded boundaries.12 In contrast t o implementations on structured and unstructured grids, Cartesian methods decouple the surface discretization from the volume mesh. This feature makes Cartesian methods well suited for the automated analysis of complex geometry problems, and consequently a promising approach to aerodynamic optimization. Melvin et developed an adjoint formulation for the TRANAIR code, which is based on the full-potential equation with viscous corrections. More recently, Dadone and Grossman presented an adjoint formulation for the Euler equations. In both approaches, a boundary condition is introduced to approximate the effects of the evolving surface shape that results in accurate gradient computation. Central to automated shape optimization algorithms is the issue of geometry modeling and control. The need to optimize complex, "real-life" geometry provides a strong incentive for the use of parametric-CAD systems within the optimization procedure. In previous work, we presented an effective optimization framework that incorporates a direct-CAD interface. In this work, we enhance the capabilities of this framework with efficient gradient computations using the discrete adjoint method. We present details of the adjoint numerical implementation, which reuses the domain decomposition, multigrid, and time-marching schemes of the flow solver. Furthermore, we explain and demonstrate the use of CAD in conjunction with the Cartesian adjoint approach. The final paper will contain a number of complex geometry, industrially relevant examples with many design variables to demonstrate the effectiveness of the adjoint method on Cartesian meshes.

Nemec, Marian↗